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This study is based on artificial intelligence technologies such as machine learning algorithms and data visualization analysis, and is committed to designing and implementing a UAV trajectory prediction model. This model uses the random forest algorithm to perform UAV trajectory regression and prediction, and uses data visualization technology to extract features and reduce dimensionality of the data. First, the existing relevant literature is reviewed, and the research status and development trends of UAV trajectory prediction are sorted out. Subsequently, a large amount of UAV transaction data from 2023 was collected and cleaned, and analyzed, preprocessed and feature extracted for this data. On this basis, the random forest algorithm was used to perform regression and prediction of UAV trajectorys. This study conducted an in-depth analysis of the accuracy and error of the model, and summarized the advantages, disadvantages and future development directions of the model.
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